Apply for Anomalo’s Unstructured Data Capabilities in Private Beta
Build trust in the data powering your Gen AI applications.
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Is Your Enterprise Ready for Gen AI?
Enterprises are sitting on a treasure trove of unstructured document data: customer support conversations, user generated content, internal documentation, and regulatory filings to name a few. But this data can be rife with data quality issues. Documents are incomplete, poorly written, or duplicated. Or content contains abusive or inappropriate language, proprietary information, or sensitive personally identifiable information. Enterprises must understand and manage the quality of this data before their Gen AI aspirations will bear fruit.
Anomalo’s Automated Document Data Quality solution helps enterprises measure and manage the quality of their document data stores. Anomalo uses foundational large language models to search for a wide range of potential data quality issues in every document (see product images). Each document is scored from 1 (lowest quality) to 10 (highest quality), with insights aggregated across entire collections, so teams can prioritize what to fix, filter, or flag.
Give your teams the confidence to build with Gen AI — on data they can trust.
Sensitive PII
Sensitive PII that is present in your transcribed customer support conversations
Customers removal requests
Customers asking to be removed from contact lists or seeking
Proprietary information
Proprietary information present in a dataset that could leak through a Gen AI application
Documents with structured metadata
Documents with structured metadata fields that are inconsistent with the document contents
Custom structured prompts
Customize the Anomalo platform using structured prompts to identify issues that are unique to your business, data, or objectives.
Enterprise-Grade Security and Deployment
Anomalo can run entirely within your Virtual Private Cloud (VPC). Our data quality solution integrates seamlessly with your cloud provider’s Model as a Services (MaaS) platform, such as AWS Bedrock, Google Vertex AI, or Azure AI to leverage state of the art large language models to assess the quality of your documents. Whichever deployment you choose, none of your data leaves an environment you control, and your data is never used to train or fine-tune models.
SaaS Deployment
For enhanced security and compliance, the product is accessed via AWS PrivateLink, Azure Private Link, or Google Private Service Connect, enabling private connectivity between virtual private clouds (VPCs) and cloud services without exposing data to the public internet.
In-VPC Deployment
The application can also be deployed to your own virtual private cloud (VPC). The product integrates seamlessly with cloud provider services for document quality assessment. Importantly, in this configuration, data remains within the enterprise’s controlled environment.
Get Started
Meet with our expert team and learn how Anomalo can help you achieve high data quality with less effort.